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Let $X_1,\ldots,X_n$ be independent identically distributed random vectors in $\mathbb{R}^d$. We consider upper bounds on $\max_x \mathbb{P}(a_1X_1+\cdots+a_nX_n=x)$ under various restrictions on $X_i$ and the weights $a_i$. When…

Probability · Mathematics 2020-08-04 Tomas Juškevičius , Valentas Kurauskas

The Bayesian framework is ideally suited for induction problems. The probability of observing $x_t$ at time $t$, given past observations $x_1...x_{t-1}$ can be computed with Bayes' rule if the true distribution $\mu$ of the sequences…

Artificial Intelligence · Computer Science 2011-11-09 Marcus Hutter

Generalized vector form factors of the pion, related to the moments of the generalized parton distribution functions, are evaluated in the Nambu--Jona-Lasinio model with the Pauli-Villars regularization. The lowest moments (the…

High Energy Physics - Phenomenology · Physics 2015-05-13 Wojciech Broniowski

We study the Euler-Frobenius numbers, a generalization of the Eulerian numbers, and the probability distribution obtained by normalizing them. This distribution can be obtained by rounding a sum of independent uniform random variables; this…

Probability · Mathematics 2013-05-17 Svante Janson

We derive bounds for the Orlicz norm of the deviation of a random variable defined on $\mathbb{R}^n$ from its Gaussian mean value. The random variables are assumed to be smooth and the bound itself depends on the Orlicz norm of the…

Statistics Theory · Mathematics 2021-01-11 Giovanni Pistone

In the paper, multivariate probability distributions are considered that are representable as scale mixtures of multivariate elliptically contoured stable distributions. It is demonstrated that these distributions form a special subclass of…

Probability · Mathematics 2019-12-05 Victor Korolev , Alexander Zeifman

It is known that each symmetric stable distribution in $R^d$ is related to a norm on $R^d$ that makes $R^d$ embeddable in $L_p([0,1])$. In case of a multivariate Cauchy distribution the unit ball in this norm corresponds is the polar set to…

Probability · Mathematics 2008-03-22 Ilya Molchanov

We investigate the average characteristic polynomial $\mathbb E\big[\prod_{i=1}^N(z-x_i)\big] $ where the $x_i$'s are real random variables which form a determinantal point process associated to a bounded projection operator. For a subclass…

Probability · Mathematics 2015-01-08 Adrien Hardy

We show that almost any one-dimensional projection of a suitably scaled random walk on a hypercube, inscribed in a hypersphere, converges weakly to an Ornstein-Uhlenbeck process as the dimension of the sphere tends to infinity. We also…

Probability · Mathematics 2009-08-26 Max Skipper

We investigate a generalized empirical likelihood approach in a two-group setting where the constraints on parameters have a form of U-statistics. In this situation, the summands that consist of the constraints for the empirical likelihood…

Methodology · Statistics 2015-05-04 Jihnhee Yu , Luge Yang , Albert Vexler , Alan D. Hutson

This note reports on some attempts to examine if and under which conditions the naturally scaled probability measures associated to an orthonormal basis of a classical Paley-Wiener space converge to a uniform distribution (on a compact set…

Mathematical Physics · Physics 2014-06-27 Kurt Pagani

We study the convergence of the empirical spectral distribution of $\mathbf{A} \mathbf{B} \mathbf{A}$ for $N \times N$ orthogonal projection matrices $\mathbf{A}$ and $\mathbf{B}$, where $\frac{1}{N}\mathrm{Tr}(\mathbf{A})$ and…

Probability · Mathematics 2023-01-24 Dmitriy Kunisky

Riemannian Gaussian distributions were initially introduced as basic building blocks for learning models which aim to capture the intrinsic structure of statistical populations of positive-definite matrices (here called covariance…

Statistics Theory · Mathematics 2023-02-16 Salem Said , Simon Heuveline , Cyrus Mostajeran

We show that for any $1\leq p\leq\infty$, the family of random vectors uniformly distributed on hyperplane projections of the unit ball of $\ell_p^n$ verify the variance conjecture $$ \textrm{Var}\,|X|^2\leq C\max_{\xi\in…

Functional Analysis · Mathematics 2016-10-14 David Alonso-Gutiérrez , Jesús Bastero

Given an Euclidean space, this paper elucidates the topological link between the partial derivatives of the Minkowski functional associated to a set (assumed to be compact, convex, with a differentiable boundary and a non-empty interior)…

Differential Geometry · Mathematics 2024-07-18 Gustave Bainier , Benoit Marx , Jean-Christophe Ponsart

In this article we reconsider the problem of the propagation of waves in a random medium in a kinetic regime. The final aim of this program would be the understanding of the conditions which allow to derive a kinetic or radiative transfer…

Analysis of PDEs · Mathematics 2022-07-28 S Breteaux , F Nier

We study the conditional distribution of low-dimensional projections from high-dimensional data, where the conditioning is on other low-dimensional projections. To fix ideas, consider a random d-vector Z that has a Lebesgue density and that…

Statistics Theory · Mathematics 2013-04-23 Hannes Leeb

Assuming that a reflected Ornstein-Uhlenbeck state process is observed at discrete time instants, we propose generalized moment estimators to estimate all drift and diffusion parameters via the celebrated ergodic theorem. With the sampling…

Statistics Theory · Mathematics 2020-09-14 Yaozhong Hu , Yuejuan Xi

We present a probabilistic proof of the mean field limit and propagation of chaos $N$-particle systems in three dimensions with positive (Coulomb) or negative (Newton) $1/r$ potentials scaling like $1/N$ and an $N$-dependent cut-off which…

Mathematical Physics · Physics 2016-06-02 Dustin Lazarovici , Peter Pickl

This paper studies Gaussian random fields with Mat\'ern covariance functions with smooth parameter $\nu>2$. Two cases of parameter spaces, the Euclidean space and $N$-dimensional sphere, are considered. For such smooth Gaussian fields, we…

Probability · Mathematics 2024-03-27 Dan Cheng
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